2c97e0436c
The eval-mode policy was producing diverse Boltzmann picks (verified by the
new `val_dir_dist` HEALTH_DIAG line) but every active-direction pick (Long /
Short) was collapsing to `actual_dir = Flat` because the Kelly cap forced
`target_position = 0` at cold start.
Cluster run `train-multi-seed-ddrpr` epoch 0 made this unambiguous:
val_dir_dist [short=0.0000 hold=0.1953 long=0.0001 flat=0.8047]
Boltzmann fired correctly (sum hold + flat ≈ 100% of bars, with Hold ~ 20% =
the share of bars where the policy explicitly picked Hold; the other 80%
were active-direction picks all rerouted to Flat by `target_position = 0`).
Root cause in `trade_physics.cuh::kelly_position_cap`:
warmup_floor = clamp(conviction, 0, 1) // ← can hit 0
effective_kelly = maturity*kelly_f + (1-maturity)*warmup_floor
= 0 + 1*0 = 0 at cold start with low conviction
cap = effective_kelly * max_position * safety = 0 → no exposure permitted
The `safety_multiplier` was already protected by a `health_safety = 0.5 + 0.5×h`
floor, but `warmup_floor` had no such floor. Catch-22: low conviction → cap=0 →
no trades → Kelly stats stay cold → conviction stays low → forever.
The same bootstrap-deadlock pattern as the IQN trunk SAXPY readiness gate
(commit f86353840), and the fix is structurally identical — apply a non-zero
adaptive floor sourced from the same training-stability signal:
warmup_floor = max(conviction, health_floor)
where `health_floor = 0.5 + 0.5 × ISV[LEARNING_HEALTH]` is the same value the
caller already computes for `safety_multiplier`. Both signals are adaptive
and ISV-driven; no tuned constants. The floor only matters during cold start
— once `maturity → 1` after ≥10 trades the term drops out entirely.
Threaded through both `apply_kelly_cap` and `kelly_position_cap` signatures;
single caller in `unified_env_step_core` passes `health_safety` as the new
arg (already locally computed two lines above). Build clean at 11-warning
baseline.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.